Projected changes in climate are likely to affect not only its mean state but also its variability. As such, improving our understanding of the spectrum of climate variability and how different feedbacks in the climate system influence it is of vital importance. We perform a process-based examination of variability with respect to changing orbital insulation, ice coverage, and land/sea distribution during the Last Glacial Maximum and the Holocene. To this end, we adapt a two-dimensional energy balance model [Zhuang, North & Stevens, 2017] to run transient simulations. The model is forced by carbon dioxide and solar insolation changes for the last Glacial cycle. We evaluate the model’s ability to reproduce changes in local to global, seasonal to millennial temperature distributions during the Last Glacial Maximum and the Holocene. We compare the simulated states and the transient evolution to those obtained by comprehensive coupled climate models. Finally, we test the mean-state dependence of temperature variability over a large range of model configurations and discuss implications for future climate.

Some oceanic and atmospheric flows may be modelled as equivalent-barotropic systems, in which the horizontal fluid velocity varies in magnitude at different vertical levels while keeping the same direction. The governing equations at a specific level are identical to those of a homogeneous flow over an equivalent depth, determined by a pre-defined vertical structure. Most oceanic studies using the equivalent-barotropic approach are focused on steady, linear formulations. In this work, the nonlinear, time-dependent model with variable topography is examined. To include nonlinear terms, we assume suitable approximations and evaluate the associated error in the dynamical vorticity equation. The model is solved numerically to investigate the equivalent-barotropic dynamics in comparison with a purely barotropic flow. We consider two problems in which the behaviour of homogeneous flows has been well-established either experimentally or analytically in past studies. First, the nonlinear evolution of cyclonic vortices around a topographic seamount is examined. It is found that the vortex drift induced by the mountain is modified according to the vertical structure of the flow. When the vertical structure is abrupt, the model effectively isolates the surface flow from both inviscid and viscous topographic effects (due to the shape of the solid bottom and Ekman friction, respectively). Second, the wind-driven flow in a closed basin with variable topography is studied (for a flat bottom this is the so-called Stommel problem). For a zonally uniform, negative wind-stress curl in the homogeneous case, a large-scale, anticyclonic gyre is formed and displaced southward due to topographic effects at the western slope of the basin. The flow reaches a steady state due to the balance between topographic, β, wind-stress and bottom friction effects. However, in the equivalent-barotropic simulations with an abrupt vertical structure, such an equilibrium cannot be reached because the forcing effects at the surface are enhanced, while bottom friction effects are reduced. As a result, the unsteady flow is decomposed as a set of planetary waves.

We present the results of the analysis of the reliability of ionosphere TEC values produced by the GNSS receiver installed at the Lisbon airport (Portugal), since 2015. The installed equipment is a NovAtel EURO4 with a JAVAD Choke-Ring antenna. The installed firmware (SCINDA) is specific for scintillation detection. We did a comparison of the SCINDA line-of-sight TEC values with the observed vertical TEC data collected (using ionosonde) by the Ebro Observatory in Spain, and with the vertical TEC values produced using the software developed in the Royal Observatory of Belgium. The differences between the ionosonde-based and GNSS-based TEC and sources of these differences are discussed. In this study special attention was paid to the epochs accompanied by significant Space Weather events strongly affected the ionosphere and the quality of the GNSS positioning.

Crop monitoring requires both high spatial resolution data (HSR) for observing within sub-parcel scale, and high temporal resolution (HTR) to monitor vegetation changes during along the crop cycle. However, these simultaneous requirements are difficult to fulfill by the same satellite. In temperate areas such as the Versailles Plain, near Paris, France, HRS data have at best a dozen images exploitable per year, even with Sentinel-2 because of cloud cover, while those with medium spatial resolution (MRS) provide daily images, but at the generally mixed pixel scale. In France, the Land Parcel Identification System (LPIS) is an information system of the crop types declared by farmers, providing reference information about the annual crops cultivated within each agricultural parcel. In this work, the objective was to monitor the phenology of annual crops recorded in the LPIS of 2016, using satellite image time series from HRS Sentinel-2 (10m) and MRS Proba-V (100m) acquired from early to end of 2016 over the Versailles Plain, a small agricultural region (221 km2) cultivated with annual crops. From the two types of time series, the temporal variations of vegetation indices (NDVI / EVI2) of crops were extracted in order to analyze the crop seasonal variations of winter wheat, winter oilseed rape and maize over 2857 parcels with average size of 6.88 ha. The linear method of spatial disaggregation was applied on the MRS data, using fractions of each crop type in the mixed pixels calculated from the 2016-LPIS. The temporal responses from HRS data were compared with those of the MRS sub-pixels. Comparisons between both time series revealed significant correlations for the three studied crops (winter wheat = 0.94, winter oilseed rape = 0.74 and maize = 0.79). By improving the temporal frequency of the monitoring, from13 images for HRS to 25 images for MRS, the disaggregated MRS time series enabled to distinguish the phenological stages of the three studied crops better than the HRS time series. In conclusion, our method of spatial disaggregation can be used to improve the exploitation of satellite data at MRS in seasonal crop monitoring, especially during the transition periods when the spectral indices of crops are likely to change quickly.

The Chilean subduction zone is one of the most seismically active regions on Earth, due to the shallow depth of the seismogenic zone in combination with the high coupling coefficients and high plate convergence rate. On February 27, 2010, the Maule earthquake, which is one of the strongest instrumentally registered megathrust earthquakes, occurred in Darwin seismic gap – a seismically calm zone existed near the coast of Chile since 1835. We use the keyboard model of generation of strong subduction earthquakes [Lobkovky et al., 1991] to analyze the peculiarities of seismic deformation cycle (SDC) related to the Darwin seismic gap and the 2010 earthquake. Keyboard structure of the South American continental margin near the source zone of the Maule earthquake is confirmed by seismological and geological data. Using of keyboard model allows us to associate interseismic, coseismic and postseismic deformations observed by satellite geodesy with the action of particular geodynamic processes and, therefore, to study their features. To achieve this aim, we analyze the data of almost 10 years of continuous observations at 76 stations of the Chilean GPS network deployed along the source zone of the 2010 Maule earthquake. The analysis of variations in surface deformation fields is based on displacement rates fields of GPS stations estimated over 1-year intervals. On the basis of registered coseismic displacements we construct a model of slip distribution in the source zone of the Maule earthquake and determine the magnitudes of instantaneous shifts of seismogenic blocks towards the ocean, which reached 1-3 meters. In the first two years after the 2010 earthquake GPS stations shift toward the ocean over the whole Central Chile region, which indicates passing of aftershock stage of the SDC. Over the next 7 years of observations, the observed displacements can be mainly explained by the process of restoring the stationary state of stress accumulation for seismogenic blocks in the frontal part of the subduction zone in combination with the continuing displacement of the rear massif by a viscous asthenospheric flow. To assess the time of transition of seismogenic zone to stationary state of accumulation of elastic stresses we construct models of frictional afterslip and viscoelastic relaxation in the asthenosphere. The durations of the afterslip and viscoelastic relaxation processes for the Maule earthquake are according to our estimates about half a year and more than 15 years respectively. Understanding of the features of the SDC plays a significant role in the seismic hazard assessment of the Maule and Biobio regions of Chile.

In this research, GRACE satellite data have been used in order to investigate the possibility of estimating the amount of groundwater used in agriculture. The level-2 data of the GRACE satellites have been used to estimate the monthly groundwater level changes in central plateau catchment in Iran during the period of 2003 to 2013. One degree grid is used along with corrections of soil moisture, canopy, rainfall and snowfall from GRACE satellite data with the CLM4 hydrology model. The results revealed the amount of current groundwater in Iran and agricultural usage from groundwater have been determined (the largest consumer of groundwaters). verification of the results has been done by comparing the GRACE satellite data and piezometric wells data. Furthermore, ArcMap (ArcGIS) software were used for data analysis.

Social scientists have a long history of documenting disasters and natural extreme events’ behavioural response through the collection of perishable post-event data (Gruntfest 1977; Quarantelli and Dynes, 1977; Stalling, 1987; Quarantelli, 1997, 2003; Drabeck, 1999). Such empirical and theoretical foundations constitute a strong background to understand crisis responses and advance our knowledge of the drivers of human behavioural responses to fast evolving weather-related events. Outputs from this field of research show that public warning and behavioural response is a social process that takes several phases before a protective action is put in place (Mileti, 1995; Trainor et al., 2008, Parker et al., 2009, Lindell et al., 2004). These authors identified factors related to the characteristics of the hazard, the warning information characteristics, the situational and personal characteristics of the receiver and the socio-cultural context as strong determinants of the public behavioural response. In fast-moving events like flash-floods, the amount of time available to detect the threat and respond to it is so limited that protective actions often consist in dealing with contingent situations triggered by the irruption of dangerous circumstances in the middle of daily life activities and routines (Ruin et al., 2008, 2009; Terti et al., 2015). Understanding how people actually detect potentially dangerous circumstances and manage to timely adapt their routine to cope with the speed of the hazard evolution remains a challenge. Based on insights from post-event interviews, online surveys were used to quantitatively document behavioural responses associated with 3 catastrophic flash flood events that happened in southern France in 2014 and 2015. The coupled analysis of responses to these surveys with hydrometeorological parameters allows to better understand the link between the event magnitude and self-protective behaviours in the context of short-fuse weather events as flash floods. Knowledge gained from such an integrated approach is necessary for drawing lessons for the development of coupled human-natural system modeling and the prediction of the human vulnerability dynamics in short-fuse weather events.

The coupled Delft3D Flexible Mesh (D3D FM) - SWAN model with an unstructured grid has been developed recently to simulate storm surge and waves; and another open source model, Telemac-Tomawac, has been widely used for storm surge and wave propagation simulation in coastal areas for more than 20 years. However, the choice of a hydrodynamic model for a specific area in terms of cost, efficiency and accuracy is often a dilemma at the beginning of a modeling project. The objective of this research is to examine the effects of two software packages in terms of accuracy and performance with a case study in the Shanghai area of China. Model performance has been assessed based on model configuration, model calibration, grid generation and computational efficiency. Comparing measured water levels with model results, both approaches were able to accurately predict hydrodynamic conditions in a complex estuarine environment. Both models showed that it can efficiently simulate hydrodynamics in the coastal area under various scenarios for further climate adaptation research. Additionally, both models were used to simulate inundation propagation due to hypothetical failures of flood defenses in the coastal area. A comparison of inundation extent and maximum inundation depth showed that they were equally well-suited for overtopping and inundation simulation.

During the analysis - funded by The European Agricultural Fund for Rural Development (EAFRD) that has financed the EU’s contribution to rural development program in Umbria (Italy) – of meteorological data from automatic weather stations following the WMO requirements [1], it has become evident the need of using the newest global climatic data (ERA5, ECMWF [2]) to compute indices to perform an extended quality control over data and to give climate information to the end users. The peculiar regional environment with strong orographic modulation of the Umbria region and the consequent impact over the precipitation field together with the signal of a seasonal and intra-seasonal change of the temperature distribution, show a complex impact of the climate change over the Umbria region and broadly over Central Italy. This work is trying to show how to account for the impact of climate change over the phenology of vineyards using different indices as SPI , SPEI, and Winkler starting from the new reanalysis dataset with enhanced resolution in time and space. Moreover, within this project agronomists and plant pathologists are cooperating with meteorological scientists to analyze and relate weather epidemic development in order to reduce the economic impact and environmental effects of airborne plant disease epidemics and ultimately to make the end-users timely decisions about the effective and economical application of fungicides and about other tactics to manage plant diseases. [1] WMO. Guide to agricultural meteorological practices (WMO-no. 134). World Meteorological Organization: Geneva, Switzerland, 2010. [2] https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era5

Deep learning techniques are used for capturing intricate structures of large-scale data by employing computational models of multiple processing layers that can learn and represent data with multiple levels of abstraction [1]. Such methods can include Convolutional Neural Networks, stacked auto-encoders and Long-Short Term Memory (LSTM) architectures. LSTM networks are suitable for dealing with time-dependent data through mapping input sequences to output sequences as it is done, for instance, in language modeling and speech recognition. One application that has recently attracted considerable attention within the geodetic community is the possibility of applying these techniques to account for the adverse effects of the ionospheric delays on the GNSS satellite signals. LSTM architectures model long-range dependencies in time series, making them appropriate for ionospheric modeling in GNSS positioning. This paper deals with a modeling approach suitable for predicting the ionospheric delay at different locations of the IGS network stations using the LSTM networks. We also incorporate a Bayesian optimization method for selecting the best configuration parameters of the LSTM network, thus improving network’s performance.

We used the process-based and tracer-aided ecohydrological model EcH2O-iso to assess the effects of vegetation cover on water balance partitioning and associated flux ages under temperate beech forest (F) and grassland (G) in Northern Germany. The model was tuned on the basis of a multi-criteria calibration against an unusually rich measured data set from a long-term monitoring site.. The calibration incorporates metrics of the energy balance, hydrological function and biomass accumulation. It resulted in good efficiency statistics for simulations of surface energy exchange, soil water content, transpiration and biomass production. The model simulations showed that the forest “used” more water than the grassland; from 620mm of average annual precipitation, losses were higher through interception (29% under F, 16% for G) and combined soil evaporation and transpiration (59% F, 47% G). As a result, groundwater recharge was greatly enhanced under grassland at 37% of precipitation compared with12% for forest. The model allowed us to track the ages of water in the different storage compartments and fluxes.In the shallow soil horizons, the average ages of soil water fluxes and evaporation were similar in both plots (∼1.5month), though transpiration and groundwater recharge were older under forest (∼6 months compared with∼3months for transpiration and∼12 months compared with∼10 months for groundwater). Flux tracking with Cl tracers provided independent support for the modelling results, though also highlighted effects of uncertainties in forest partitioning of evaporation and transpiration. This underlines the potential for tracer aided ecohydrological models in land use change studies. By tracking storage – flux – age interactions under different land covers, the effects on water partitioning and age distributions can be quantified and the implications for climate change assessed.Better conceptualisation of soil water mixing processes, and improved calibration data on leaf area index and root distribution appear obvious respective modelling and data needs for improved model results.

Changes in the quantity and quality of groundwater and water in the hydrological cycle in general have important implications for the evolution of water resources, the built environment, and terrestrial and aquatic ecosystems, globally. Exploitation of groundwater and other subsurface resources may lead to e.g. land subsidence, salt water intrusion, loss of important terrestrial and aquatic ecosystems and hence biodiversity. Together with biogeochemical flows of nitrogen and phosphorus and changes in the land-system and climate, these are currently considered the main environmental problems of the planet, which are breaching or close to breaching planetary boundaries. Changes in the hydrological cycle including groundwater is closely related to and affecting these changes. It is the ambition of the four GeoERA groundwater projects studying aspects of groundwater quantity and quality issues related to natural processes and human activities to further develop the European Geological Data Infrastructure as a leading information platform for groundwater data in Europe and one of the leading platforms, globally. Here we briefly present the contents and objectives of the four groundwater projects: HOVER - Hydrogeological processes and geological settings over Europe controlling dissolved geogenic and anthropogenic elements in groundwater of relevance to human health and the status of dependent ecosystems; RESOURCE - Resources of groundwater, harmonized at cross-border and Pan-European Scale; TACTIC – Tools for assessment of climate change impact on groundwater and adaptation strategies and VoGERA - Vulnerability of shallow groundwater resources to deep sub-surface energy-related activities. The four projects will deliver “FAIR” (Findable, Accesssible, Interoperable and Reusable) data and information via the European Geological Data Infrastructure easily accessible for all relevant endusers. This will improve our understanding of the subsurface and support common efforts for developing geoethical uses of the subsurface.

Apples and pears represent an important share of Belgium’s horticultural production but the sector has been subjected to a range of challenging meteorological conditions over the past decade. The most disastrous event was the extraordinarily severe frost night happening during peak flowering of commercially grown apple cultivars, in April 2017. This research aims at investigating how meteorological hazards in Belgium will evolve in space and time with changing climate and at challenging the claim of the insurance sector that the hazards are spatially invariant. It features the assessment of the probability and severity of frosts during the flowering period throughout the 21st century, using a set of regional climate model realizations from the CORDEX ensemble. To this end, the apple and pear tree phenology is modelled using the strong relation between air temperature during winter/early spring and dormancy break and consequently flowering. Local observations since 1950 of the phenology of major cultivars indeed confirm a shift in phenological stages in relation to warmer winters as an effect of climate change. Preliminary results from sequential phenological models, running on future daily mean temperatures, suggest that both the onset of flowering and the last frost event in spring are likely to occur earlier in the year, so that the challenge is to determine which trend is dominant and how the return periods of severe frost nights (< -2◦C) during sensitive stages evolve. Thereby, differences between cultivars and between orchard locations within Belgium are taken into consideration. Furthermore, the potential impact of shifting temperature regimes on the pollinator activity during the blossom period is taken into account, knowing that the most commonly commercially employed bee species are sensitive to colder and more variable temperatures. The distinct resulting hazard maps can be used to support decision making regarding adaptation and prevention measures at the field, farm and regional scales. Further downscaling will be possible by considering local pedologic and topographic conditions, while for validation, data about damage compensation claims will be used.